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"Why six decades? Well the authors wanted to go back as far as they could while still accessing high-quality records of the ice extent. They used three different sets of data that record the extent of ice in the region." One of the three data sets used by Mueller et al. is the one we published two years ago and that Neven kindly reblogged here: (Journal article: , NetCDF file with the gridded data: , CSV file with the extent values: Glad to see that our data are useful!
Toggle Commented Sep 7, 2018 on Aerosols and Arctic sea ice loss at Arctic Sea Ice
This is the latest graph from the PIOMAS team comparing their April results with those from Cryosat-2: Since January, the difference has narrowed. However, it still exists.According to PIOMAS, the volume in April 2017 is the lowest of the time series. On the contrary, according to Cryosat-2, the volume is the third lowest, very close to April 2012, 2013 and 2016.
Toggle Commented Jun 5, 2017 on PIOMAS June 2017 at Arctic Sea Ice
Diablobanquisa is now following Neven
Nov 21, 2016
Thanks for everything, Rob, I have really enjoyed this thread too.
I've also extracted your August numbers and plotted them against your and our results for September (click for a larger version):
And this is the graph comparing with Meier et al. (click for a larger version):
Thank you for your work, Rob. Diablo, I do not have the numbers for Meier et al and your reconstruction, so could you please provide a 'final' overview plot of how our reconstructions of Arctic sea ice in September from 1935 to present day differ ? If you need my exact numbers for 1935-1978, please let me know and I can send them to you (if I know your email) or post them here. I have extracted your extent numbers from the graph you posted above. It's not exact, but I think it should be accurate enough for these comparison purposes. Just to check I did it right: your lowest pre-satellite value is 1941 around 6.42 M km^2? And the highest is 1963 with 8.78 M km^2? (Alternatively, you can download our numbers from: and plot them yourself). The graph below compares Walsh et al. 2016 (blue), my results (red) and yours (black), for September 1935-2013 (click for a larger version): I think that the three time series look pretty consistent. Regarding some of your comments: First thing to note is that the September reconstruction more closely follows Walsh reconstruction than for August. That's probably since September does not use Kelly fields, and this suggests that the August Kelly fields in Walsh reconstruction are really no good. I agree. Another indication that that 'up-trend' in the 19th century is not real is the August-minus-September graph plotted in blue : before 1900 the difference between August and September appears to go up, which is very unlikely to be realistic. I consider my September reconstruction a lower bound for ice extent since 1850. Maybe the difference with Walsh' original which is (for pre-1900) more based on a fixed 'climatology', the difference between the graphs is an indication of the uncertainty in observation. I think that Walsh et al. and you have done a great work reconstructing the 1850-1934 period. However, I think that even August data before 1935 must be taken with a grain of salt. And I wouldn't put too much faith in any results before 1900: there are simply no enough direct observations available. I think the uncertainties and error margins before 1900 are huge.
Great work, Rob! It seems that your algorithm works fine. In the meantime, I have noticed that the new HadISST2 Sea Ice Concentration dataset is available for download: In 2014, Titchner and Rayner published a paper presenting the Sea Ice Concentration component of the new HadISST2 dataset: Titchner, H. A., and N. A. Rayner (2014), The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations, J. Geophys. Res. Atmos., 119, 2864-2889, doi: 10.1002/2013JD020316. However, until recently the gridded data haven't became publicly available. Titchner and Rayner relied mostly on the old Walsh dataset, and they didn't incorporate AARI data. Titchner and Rayner have performed a sort of 'reverse adjustment'. That is, they have adjusted the satellite data to 'match' with the pre-1979 values. However, their results look rather strange. The graph below compares HadISST2 extent numbers for September Arctic SIE (blue line) against those from Walsh et al. 2016 (black line) and our paper (red line) (click for a larger version): Even if we adjust back the whole timeseries to match with the satellite data since 1979, HadISST2 still looks a bit strange (click for a larger version): I'd dare to say that, after the publication of Walsh et al. 2016 (and our paper, and Rob's findings), the Arctic SIC data of HadISST2 is already obsolete and needs an update.
Great regional analysis, Rob! Although it is interesting that pre-1930, ice extent remains rather flat, although Arctic temperatures were certainly on the rise there. From 1880 to 1920 the temperature looks also rather flat. It seems to me that the significant warming started around 1920. The ice then should be older and thicker, and maybe the effects of that warming didn't become noticeable on late summer extent numbers until the 30s. Anyway, I also think that the August extent numbers before the 30s are less reliable. Before mid 30s, AARI charts aren't available anymore, and the only direct observations are those from ACSYS and DMI charts, so the reconstruction relies more heavily on your match and merge algorithm. To be totally fair, the last reconstruction I will make will be one where I ignore the Walsh&Johnson source in the 1953-1979 period, and let my Match-and-Merge algorithm do the work. That would be a fair comparison between pre- and post-1953 reconstruction, and I'm curious how pronounced the 'dip' remains with that. I have some concerns about this, since I think that you have used the 1953-2000 period for analogs. So, your algorithm could have imported to 1935-1952 some data from 1953-1978 that now you are planning to exclude and replace with analogs from 1979-2000. Maybe, to be totally fair, I think that you could use the 1979-2000 period for analogs for the whole 1850-1978 period. Although your cpu would need at least 25 hours more of work... ;-) Either way, the results will be interesting, of course. Cheers
Great work, Rob! And I´m glad to see that finally your results are consistent with ours.
Could you still send this info to Florence Fetterer for correction in a future version of the data set ? Hi Rob, yes, I will let her know. In the meantime, Walsh et al. have published a paper presenting their dataset: As we already knew, the data and the documentation are available here:
Excellent, Rob, thank you for your work. I'm sorry for my silence and long delays, but presently I'm too busy. When I have more time for this (I don't know when...) I will read again and more carefully everything you have posted since April 19. I will have to think about it, and I guess I'll come with some comments, questions, and suggestions. Cheers PS: a couple of weeks ago I sent an email to Florence Fetterer in order to let her know the 'misplaced Kelly fields' issue. She answered me that they will look into it. I also mentioned the well known 'consistency issue' between pre-satellite and satellite data and she told me that she hopes they'll be able to address that with a new version over the coming year.
('adjusted values' to match Walsh satellite numbers, since you are using them)
Hi Rob, I´m sorry, but currently I am too busy and I don't have much time. Great work! Just a couple of comments/suggestions after a quick reading: - Are you looking for 'analogs' on the 'unadjusted' values for 1953-1978? If that is the case, I think you should use the 'adjusted' ones (in order to avoid 'exporting' the 'concentration bias' and to keep the extent numbers consistent throughout the whole 1935-2013 period).(Alternatively, you could 'adjust' the 'concentration bias' on the 'analog' after finding it) - Maybe you could test your algorithm using some years with a known result. For instance, you could take any year from the satellite era (or even from 1953-1978), remove everything except the Siberian Sector and look for analogs. And then, check whether the result matches the actual extent. (That would test September. You could also remove everything except the Siberian sector and some patches at Greenland, Svalbard, Baffin... simulating those August months when DMI and ACSYS direct observations are available. Look for analogs and check the result.) Cheers
Bill, "Nihil obstat" from me. Rob, I think that, after adjusting the 'Walsh&Johnson' source, the 1953-1978 period is rather reliable already. (and I think it's very similar to the result presented on our paper, and already better than Meier et al. since they didn't integrate AARI data). So, at this point, maybe I'd be more interested in the 1935-1952 period.
August 1972-78 ESMR numbers adjusted to match Walsh's satellite data: 8.61, 8.53, 8.19, 7.98, 8.29, 7.65, 8.24.
Hi Rob, - The homogenized 72-78 numbers for August (those that match NSIDC Sea Ice Index) are: 8.28, 8.2, 7.86, 7.65, 7.96, 7.32, 7.91. (Right now, I can't calculate the numbers to match Walsh's satellite data, I'll post them later) - Regarding AARI data, although I think that they are more consistent with passive microwave readings, I agree that we could try to adjust them as well, if neccesary. How do you suggest doing it? (I'm thinking that maybe the best approach to adjust both Walsh&Johnson and AARI sources could be testing them against ESMR gridded data: Of course, it is a more difficult approach. If we do this, we should also check whether ESMR maps match Cavalieri numbers, and if that is the case we should use for the satellite era Cavalieri's numbers themselves.) ( - Moving to 1935-1952, I'm thinking that, when Walsh uses analogs from 1953-1978 to infill the missing areas during September 1935-1952, he is actually 'importing' the 'concentration bias' from the Walsh&Johnson source. I think it deserves an adjustment. However, we don't know which analogs were used for each year... pre-satellite, satellite, a mix...Anyway, when I have some time, I'll look at Walsh's September 35-52 maps looking for the 'concentration bias footprint', that should be a wider and 'blueish' Marginal Ice Zone. Any ideas about this issue? )
Excellent Rob, you've done a great work adjusting directly for the 'ice-concentration' bias of the 'Walsh&Johnson' source. However, a couple of comments: - I think that in your graph you are using Walsh's satellite numbers from 1979 onwards. However, the homogenized ESMR values I posted above (7.59, 7.42, 7.25, 7.62, 7.42, 7.26, 7.29) are adjusted to match NSIDC's Sea Ice Index. So you should use Sea Ice Index from 1979 onwards ( (Sea Ice Index values are 0.23 M km^2 lower than Walsh's ones). (Alternatively, you could use the Walsh's satellite numbers, but adjusting the concentration before 1979 in order to match the 1972-1978 adjusted ESMR values that match Walsh's satellite numbers: 7.82, 7.65, 7.48, 7.85, 7.65, 7.49, 7.52) - Now, 1935-1952 left. That's a different story.
Finally, I adjusted the 1935-1978 Walsh's original values by subtracting 0.28, so that the 1972–1978 period is consistent with Walsh's satellite numbers post-1978. 1972 (Meier and us adjusted the 1953-1971 period by assuming the same bias than during 1972-1978)
Table 1 does list the Canadian Meteorological Service. Are these the same charts ? I'm not sure whether they are the same charts I posted above: (Weekly Regional Ice Charts - Black and White, from 1968 onwards). Either way, they could be useful to 'calibrate' the Walsh and Johnson source. However, CIS Ice Charts could also have their own 'bias' when compared with passive microwave data: Did you subtract a scalar that best matches the Walsh numbers with ESMR numbers over the training period (1972-1978) or did you do something 'gridded' ? Nothing gridded, just a subtraction (but not directly to match ESMR, but to match 'adjusted' ESMR). Firstly, I took Cavalieri's numbers (1972-2002) and Walsh's satellite numbers (1979-2013), and I calculated their mean difference during the overlapping period 1979-2002: Walsh's numbers are 0.35 M km^2 higher. Secondly, I adjusted the 1972-1978 Cavalieri's numbers by adding 0.35, in order to match Walsh's satellite values post-1978, so that I obtained a consistent time series from 1972 to 2013 (CW7213). Thirdly, I calculated the mean difference during 1972-78 between Walsh's original numbers and CW7213 ones (Walsh's numbers are 0.28 M km^2 higher). Finally, I adjusted the 1935-1978 Walsh's original values by subtracting 0.28, so that the 1972–1978 period is consistent with Walsh's satellite numbers post-1978. The same method could be used to obtain 72-78 values consistent with any satellite dataset. For instance, in order to match NSIDC's monthly means, 0.51 M km^2 must be subtracted from the Walsh's original 1972-1978 numbers.
I agree, Rob.
According to Mahoney's Fig. 6, 1937 is the highest summer value. For instance, it's higher than 1949. I wonder how they reached that conclusion from AARI maps: (September, 1937 vs. 1949; if we look at August, it's the same)
Regarding Mahoney, honestly I don't understand how they 'infilled' their many 'missing' seas and months during the 30s and early 40s in order to get their overall numbers for the whole domain. And I think that they have missed reliable data that could be helpful to reduce the 'missing' seas and months. For instance, they don't give a number for ESS and Chukchi in September 1937, but I think that the map posted above allows an estimate. In summary, I don't understand their results for the earlier part of the record.
Regarding Kelly fields, I am more skeptic. Even if we use the right ones, I don't think they are a reliable source, but a guess at best. (I say 'at best' because from 1939 onwards the white coloured areas on DMI charts they are derived from, don't look like an estimate at all, but just like an 'area without data')